Journal article
Enhancing the performance of existing urban traffic light control through extremum-seeking
R Kutadinata, W Moase, C Manzie, L Zhang, T Garoni
Transportation Research Part C Emerging Technologies | Published : 2016
Abstract
Urban traffic light controllers are responsible for maintaining good performance within the transport network. Most existing and proposed controllers have design parameters that require some degree of tuning, with the sensitivity of the performance measure to the parameter often high. To date, tuning has been largely treated as a manual calibration exercise but ignores the effects of changes in traffic condition, such as demand profile evolution due to urban population growth. To address this potential shortcoming, we seek to use a newly developed extremum-seeker to calibrate the parameters of existing urban traffic light controllers in real-time such that a certain performance measure is op..
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Grants
Awarded by National Computational Infrastructure
Funding Acknowledgements
This work was supported under the Australian Research Councils Linkage Projects funding scheme (project number LP120100258), and T.G. and C.M. are the recipients of Australian Research Council Future Fellowships (project numbers FT100100494 and FT100100538). This research was undertaken with the assistance of resources provided at the NCI National Facility through the National Computational Merit Allocation Scheme supported by the Australian Government.